Skip to main content
SpringerLink
Log in

The Multi-Optimized Parameter Technique for Near Online Automatic Determination of Geomagnetic Sudden Commencement Arrival Time

  • Research Article-Electrical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

This paper introduces a new technique in the automatic detection of storm sudden commencement (SC) using the discrete wavelet transform (DWT). A geomagnetic storm is a global simultaneous phenomenon affecting the whole Earth, which means that all ground magnetometers running online will record this event. An algorithm using different characteristic features of the SC is proposed. The selection of an optimal threshold for feature parameters is critical for the success of SC automatic detection. Therefore, this paper uses particle swarm optimization (PSO) to determine the optimal feature threshold values. The developed algorithm is based on data records from a network of ground magnetometers. This algorithm is implemented via multi-resolution analysis (MRA) of the DWT using the Haar wavelet filter. Four-year data sampled at one sample/s from six ground stations from low to high latitudes were analyzed to develop and test this technique. Data representing 450 days from five stations operating simultaneously are available. The confusion matrix of all possible outcomes shows that the accuracy of the proposed algorithm is 97.33%.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Shinohara, M.; Kikuchi, T.; Nozaki, K.: Automatic realtime detection of sudden commencement of geomagnetic storms. J. National Inst. Inf. Commun. Technol. 52(3/4) (2005)

  2. Chapman, S.: On the times of sudden commencement of magnetic storms. Proc. Phys. Soc. London 30(1), 205 (1917)

    Article  Google Scholar 

  3. Araki, T.: A physical model of the geomagnetic sudden commencement. Geophys. Monograph Am. Geophys. Union 81, 183–183 (1994)

    Google Scholar 

  4. Moos, N.A.F.: Magnetic Observations Made at the Govt. Observatory, Bombay, for the Period 1846–1905 and Their Discussion, Part II. (1910)

  5. Takano, S.; Minamoto, T.; Arimura, H.; Niijima, K.; Iyemori, T.; Araki, T.: Automatic detection of geomagnetic sudden commencement using lifting wavelet filters. pp. 242–251 (1999)

  6. Mendes Jr., O.; Domingues, M.O.; Da Costa, A.M.; De Gonzalez, A.L.C.: Wavelet analysis applied to magnetograms: singularity detections related to geomagnetic storms. J. Atmos. Solar Terr. Phys. 67(17–18), 1827–1836 (2005)

    Article  Google Scholar 

  7. Khabarova, O.; Pilipenko, V.; Engebretson, M. J.; Rudenchik, E.: Solar wind and interplanetary magnetic field features before magnetic storm onset, Vol. 8, pp. 1–6 (2006)

  8. Hafez, A.G.; Ghamry, E.: Automatic detection of geomagnetic sudden commencement via time–frequency clusters. Adv. Space Res. 48(9), 1537–1544 (2011)

    Article  Google Scholar 

  9. Hafez, A.G.; Ghamry, E.; Yayama, H.; Yumoto, K.: Un-decimated discrete wavelet transform based algorithm for extraction of geomagnetic storm sudden commencement onset of high resolution records. Comput. Geosci. 51, 143–152 (2013)

    Article  Google Scholar 

  10. Segarra, A.; Curto, J.: Automatic detection of sudden commencements using neural networks. Earth Planets Space 65(7), 791–797 (2013)

    Article  Google Scholar 

  11. Bailey, R.L.; Leonhardt, R.: Automated detection of geomagnetic storms with heightened risk of GIC. Earth Planets Space 68(1), 1–13 (2016)

    Article  Google Scholar 

  12. Al-Jarrah, M.A.; Yaseen, M.A.; Al-Dweik, A.; Dobre, O.A.; Alsusa, E.: Decision fusion for IoT-based wireless sensor networks. IEEE Internet Things J. 7(2), 1313–1326 (2019)

    Article  Google Scholar 

  13. Al-Jarrah, M.A.; Al-Dweik, A.; Ikki, S.S.; Alsusa, E.: Spectrum-occupancy aware cooperative spectrum sensing using adaptive detection. IEEE Syst. J. (2019)

  14. Liu, S.; Wang, K.; Liu, K.; Chen, W.: Noncoherent decision fusion over fading hybrid MACs in Wireless Sensor Networks. Sensors 19(1), 120 (2019)

    Article  Google Scholar 

  15. Yumoto, K.: MAGDAS project and its application for space weather. ilws: p. 399 (2006)

  16. Curto, J.; Araki, T.; Alberca, L.: Evolution of the concept of sudden storm commencements and their operative identification. Earth Planets Space 59(11), 1–12 (2007)

    Article  Google Scholar 

  17. Tsunomura, S.: Characteristics of geomagnetic sudden commencement observed in middle and low latitudes. Earth Planets Space 50(9), 755–772 (1998)

    Article  Google Scholar 

  18. Takeuchi, T.; Araki, T.; Viljanen, A.; Watermann, J.: Geomagnetic negative sudden impulses: interplanetary causes and polarization distribution. J. Geophys. Res. Space Phys. 107(A7), SMP-7 (2002)

    Article  Google Scholar 

  19. Chapman, S.: An outline of a theory of magnetic storms. Proc. R. Soc. Lond. Ser. Contain. Papers Math. Phys. Character 95(666), 61–83 (1918)

    Google Scholar 

  20. Percival, D.B.; Walden, A.T.: Wavelet methods for time series analysis, vol. 4. Cambridge University Press, Cambridge (2000)

    Book  Google Scholar 

  21. Jach, A.; Kokoszka, P.; Sojka, J.; Zhu, L.: Wavelet-based index of magnetic storm activity. J. Geophys. Res. Space Phys. 111, A09215 (2006). https://doi.org/10.1029/2006JA011635

    Article  Google Scholar 

  22. Hafez, A.G.; Ghamry, E.; Yayama, H.; Yumoto, K.: Systematic examination of the geomagnetic storm sudden commencement using multi resolution analysis. Adv. Space Res. 51(1), 39–49 (2013)

    Article  Google Scholar 

  23. Shi, Y.; Eberhart, R.C.: Fuzzy adaptive particle swarm optimization. In: Proceedings of the 2001 congress on evolutionary computation (IEEE Cat. No. 01TH8546). (2001)

  24. Blondin, J.: Particle swarm optimization: A tutorial. from site: http://cs.armstrong.edu/saad/csci8100/psotutorial.pdf (2009)

  25. Santra, A.; Christy, C.J.: Genetic algorithm and confusion matrix for document clustering. Int. J. Comput. Sci. Issues (IJCSI) 9(1), 322 (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Communication and Computer Department, Faculty of Engineering, Nahda University, Beni Suef, Egypt

    Sarah A. Elgiddawy & Ali G. Hafez

  2. National Research Institute of Astronomy and Geophysics, Helwan, Cairo, Egypt

    Ali G. Hafez, Ahmed Lethy & Omar M. Saad

  3. LTLab, Inc., 1-30-3 Higashi-aburayama, Fukuoka, 814-0155, Japan

    Ali G. Hafez

  4. Department of Electronics and Communications, Faculty of Engineering, Minia University, Minia, Egypt

    Ashraf A. M. Khalaf & Hesham F. A. Hamed

  5. Space Environment Research Center, Kyushu University, Fukuoka, Japan

    Akimasa Yoshikawa

  6. Department of Telecommunications Eng, Egyptian Russian University, Badr City, Egypt

    Hesham F. A. Hamed

Authors
  1. Sarah A. Elgiddawy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ali G. Hafez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ahmed Lethy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Omar M. Saad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ashraf A. M. Khalaf
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Akimasa Yoshikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hesham F. A. Hamed
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ali G. Hafez.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elgiddawy, S.A., Hafez, A.G., Lethy, A. et al. The Multi-Optimized Parameter Technique for Near Online Automatic Determination of Geomagnetic Sudden Commencement Arrival Time. Arab J Sci Eng 46, 901–908 (2021). https://doi.org/10.1007/s13369-020-04773-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-020-04773-3

Keywords

Search

Navigation